Agent skill

Cloud Screencast

by oratis in oratis/LISA

Record a clean product demo video of a web app on a disposable cloud VM — provision a GCE instance, install Xvfb + Chrome + ffmpeg + real fonts, deploy the app, drive the UI deterministically with…

MITAuto-check: warningsMedia & Creative

Install Cloud Screencast

The automated check flagged lines worth reading first. See the safety section below.

skills CLI
$ npx skills add oratis/LISA --skill cloud-screencast -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install oratis/LISA cloud-screencast --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/oratis/LISA.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/cloud-screencast .claude/skills/cloud-screencast && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
cloud-screencast
GitHub stars
175
Token cost
~3.1k tokens
SKILL.md length
1,359 words
Files
6
Skills in repo
1
Repo updated
First seen
Licence
MIT

At a glance

Record a clean product demo video of a web app on a disposable cloud VM — provision a GCE instance, install Xvfb + Chrome + ffmpeg + real fonts, deploy the app, drive the UI deterministically with…

  • Works in 9 steps: Pick the geometry first → Provision → Deploy the app + secrets → …
  • Asked to record a demo / screencast / promo video
  • SKILL.md covers Config, 1. Pick the geometry first, 2. Provision and 3. Deploy the app + secrets, plus 8 more sections
  • Runs Shell and JavaScript scripts from its folder; calls gcloud, ssh and ffmpeg; needs API_KEY

What it does

Cloud Screencast is an agent skill from oratis/LISA. Record a clean product demo video of a web app on a disposable cloud VM — provision a GCE instance, install Xvfb + Chrome + ffmpeg + real fonts, deploy the app, drive the UI deterministically with Playwright over CDP while x11grab records, then cut the raw take into a social-ready clip with speed ramps and burned-in captions. Use when asked to record a demo / screencast / promo video, produce a GIF or clip of a UI, or capture a reproducible app walkthrough — and especially when the local machine is unsuitable…

Its SKILL.md is about 3.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files (for example `reference/edit.sh`, `reference/music.sh` and `reference/setup.sh`).

It sits in Media & Creative, covering Video production. It works with FFmpeg, Playwright, Model Context Protocol and OpenAI. The repository describes itself as: Open-source AI Personal Assistant for planning, writing and personal knowledge. Use LISA Cloud or connect your own Mac. The licence is MIT.

When your agent uses it

  • Asked to record a demo / screencast / promo video
  • Capture a reproducible app walkthrough — and especially when the local machine is unsuitable (personal bookmarks and profile chrome in frame
  • Wrong window size
  • The app must start from a pristine state

Example prompts

  • “/cloud-screencast”

Requirements

  • Node.js
  • A Bash shell
  • A credential in API_KEY
  • Pre-approved tools (allowed-tools): Read, Write, Edit, Bash

Workflow steps

9 steps, taken from the step headings in SKILL.md.

  1. Pick the geometry first
  2. Provision
  3. Deploy the app + secrets
  4. Bring the stack up
  5. Drive it
  6. Record
  7. Cut
  8. Music (optional)
  9. Tear down — required

What it can do on your machine

Read from SKILL.md and the folder at commit fa44994. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Write
    • Edit
    • Bash

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships script files (Shell and JavaScript), which the agent can run.

    Shell commands in SKILL.md call:

    • gcloud
    • ssh
    • ffmpeg

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use gcloud and ssh, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • API_KEY

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Cloud Screencast loads about 3.1k tokens when it runs. Until then it costs about 176 tokens; SKILL.md has 1,359 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~176
When it runs · the whole SKILL.md, loaded when a task matches
~3.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: warnings

The automated check found patterns that need a careful read before installing.

  • WarningMentions a credentials file (SSH keys, cloud or package-manager tokens)SKILL.md:103
    ssh -i ~/.ssh/google_compute_engine -o StrictHostKeyChecking=no <user>@<EXTERNAL_IP>
  • NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
    allowed-tools: Read, Write, Edit, Bash

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from oratis/LISA at commit fa44994, republished under its MIT licence (© oratis). 1,359 words, ~3,058 tokens.

Download SKILL.mdSave it as .claude/skills/cloud-screencast/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.
name
cloud-screencast
description
Record a clean product demo video of a web app on a disposable cloud VM — provision a GCE instance, install Xvfb + Chrome + ffmpeg + real fonts, deploy the app, drive the UI deterministically with Playwright over CDP while x11grab records, then cut the raw take into a social-ready clip with speed ramps and burned-in captions. Use when asked to record a demo / screencast / promo video, produce a GIF or clip of a UI, or capture a reproducible app walkthrough — and especially when the local machine is unsuitable (personal bookmarks and profile chrome in frame, wrong window size, the app must start from a pristine state, or the recording would tie up the user's desktop for minutes).
allowed-tools
Read, Write, Edit, Bash

cloud-screencast — reproducible UI demo videos on a throwaway VM

Records a web UI on a headless cloud box instead of the user's desktop. You get a pristine app state, a chosen viewport, no personal data in frame, and a scripted take you can re-run until it's right — none of which is true of a hand-recorded local screen capture.

Cost + lifecycle: this creates a billable VM. Always tell the user it exists, and delete it when the recording is downloaded (§8). An e2-standard-4 left running is roughly $95/month.


Config

Fill once per project, then run.

PROJECT   = <gcp-project-id>
ZONE      = <zone, e.g. us-central1-a>
VM        = <instance-name, e.g. app-record>
APP_REPO  = <git url of the app, or an npm package name>
APP_START = <command that serves the UI, e.g. node dist/cli.js serve --web --port 5757>
APP_URL   = <local url the browser opens, e.g. http://127.0.0.1:5757/>
SECRETS   = <local env file the app needs, e.g. ~/.app/config.env>

1. Pick the geometry first

Everything downstream depends on this, and getting it wrong means re-recording.

Chrome's --force-device-scale-factor=N divides the X display into CSS pixels:

CSS viewport = Xvfb resolution / DSF

Record at 2× the delivery resolution and downscale in post — supersampling is what makes small UI text look sharp in an H.264 clip.

DeliveryXvfbDSFCSS viewportNotes
1920×10802880×162021440×810good default, 16:9
1920×10802560×144021280×720tighter; short UIs get clipped
1080×10802160×216021080×1080square, better mobile in-feed

Do not just use 1280×720. A real user's browser window is far taller than 720 CSS px, so a 720-tall viewport clips panels that never clip in real life — and the clipped part is usually the payoff (the final state, the confirm button). Probe the actual content height before committing (§4) and go taller if it overflows.

Keep integer DSF values. Fractional scale factors make Chrome's text rendering noticeably softer.

2. Provision

bash
gcloud compute instances create <VM> --project=<PROJECT> --zone=<ZONE> \
  --machine-type=e2-standard-4 \
  --image-family=ubuntu-2404-lts-amd64 --image-project=ubuntu-os-cloud \
  --boot-disk-size=50GB --boot-disk-type=pd-balanced \
  --labels=purpose=demo-recording

4 vCPU is the floor — x11grab at 2880×1620/30fps plus Chrome plus the app will saturate 2 cores. Copy reference/setup.sh over and run it: it installs Xvfb, ffmpeg, Chrome, xdotool, ImageMagick, Node, and — critically — fonts.

Fonts are the whole ballgame for "does this look right". Most web UIs specify -apple-system, BlinkMacSystemFont, "SF Pro Text" and ui-monospace, "SF Mono", Menlo. None of those exist on Linux, so you get DejaVu fallback and the app looks subtly wrong in a way reviewers notice but can't name. Install fonts-inter (a near-exact SF Pro substitute, and often already in the CSS fallback chain), fonts-jetbrains-mono, fonts-noto-color-emoji (UIs lean on ❤️ 🌙 ★ far more than you expect), and fonts-noto-cjk. Then fc-cache -f.

gcloud compute ssh is flaky under load. It intermittently dies with RemoteDisconnected. Fall back to plain SSH against the external IP with the key gcloud already provisioned:

bash
ssh -i ~/.ssh/google_compute_engine -o StrictHostKeyChecking=no <user>@<EXTERNAL_IP>

3. Deploy the app + secrets

Prefer building from source at the version you want to show — a published package often lags the current version.

Never put secrets in instance metadata or in a command line. Metadata is readable by anyone with project viewer, and argv shows up in ps and shell history. Pipe them over SSH's stdin instead:

bash
grep -E '^(API_KEY|BASE_URL)=' <SECRETS> | \
  ssh ... "mkdir -p ~/.app && cat > ~/.app/config.env && chmod 600 ~/.app/config.env"

Snapshot the pristine state before the app ever runs. First-run flows — onboarding, setup wizards, a birth ritual — happen exactly once, and you will need three or four takes to get one good one:

bash
cp -r ~/.app ~/.app-pristine     # BEFORE first launch
# each retake starts with:  rm -rf ~/.app && cp -r ~/.app-pristine ~/.app

4. Bring the stack up

reference/stack.sh does Xvfb → app → Chrome, idempotently. Chrome flags that matter for a clean frame:

--kiosk                      no tabs, no URL bar, no bookmarks
--hide-scrollbars            scrollbars read as clutter on video
--force-device-scale-factor  see §1
--lang=en-US                 UIs branch on navigator.language; pin it
--remote-debugging-port=9222 so Playwright can attach
--user-data-dir=/tmp/...     fresh profile, no first-run bubbles
--disable-features=Translate,TranslateUI,AutofillServerCommunication,MediaRouter

Also xsetroot -solid '<app-bg-color>' so any gap looks deliberate, and xset -dpms s off s noblank so the screen never blanks mid-take.

Then probe before recording — check the content actually fits:

js
await page.evaluate(() => ({
  viewport: [innerWidth, innerHeight], dpr: devicePixelRatio,
  overflow: document.querySelector('<container>').scrollHeight,
  clientH:  document.querySelector('<container>').clientHeight,
}))

If scrollHeight > clientHeight on something that shouldn't scroll, go back to §1.

5. Drive it

Attach to the running Chrome rather than letting Playwright launch its own — the browser then survives a script crash, so a failed drive doesn't cost you the whole recording:

js
const b = await chromium.connectOverCDP('http://127.0.0.1:9222');
const page = b.contexts()[0].pages()[0];

Use playwright-core (no bundled browser download). Rules that make takes usable:

  • Print a MARK <label> <seconds> timeline. The edit is driven entirely by these timestamps; without them you are scrubbing a 6-minute file by hand.
  • Record -draw_mouse 0. A programmatically driven cursor never moves, so a visible pointer just looks frozen.
  • Type with { delay: 40-60 }. Instant fill() looks like a bug.
  • Hold 2–3s on each payoff state. You can always cut time out in post; you cannot add a frame that was never captured.
  • Poll for real completion, not fixed sleeps — watch for text length going stable, a class appearing, an element count changing.
  • Scroll cinematically: for (i=0..N) el.scrollTop = total*i/N with a ~50ms gap reads as a deliberate camera move; a single jump reads as a glitch.

6. Record

ffmpeg runs for the whole take; you cut afterwards.

bash
ffmpeg -y -f x11grab -draw_mouse 0 -framerate 30 -video_size <W>x<H> -i :99.0 \
  -c:v libx264 -preset ultrafast -crf 16 -pix_fmt yuv420p /tmp/raw.mp4

ultrafast + crf 16 keeps capture real-time on 4 vCPU; quality is recovered in the encode pass. Stop it with SIGINT (not SIGKILL) so the container finalizes.

Beware orphaned ffmpeg. If the drive script dies, its ffmpeg child keeps recording and holds the output file — every later take then silently writes nowhere. Start each take with pkill -f x11grab.

Launch long takes detached or the SSH session ending kills them:

bash
ssh ... 'setsid bash ~/take.sh > ~/take.log 2>&1 < /dev/null & disown; exit 0'

Do not try to chain sed/mv/launch in one backgrounded compound — the & breaks the chain and you get a half-applied state that looks like it worked. Write the script to a file, scp it, run it.

Show full SKILL.md (548 more words)Show less

7. Cut

reference/edit.sh turns the raw take plus the MARK timeline into a clip: extract each beat, apply a speed ramp, concat, burn captions, downscale.

Cut with the trim filter, never -ss/-to. Both shortcuts fail silently here and you only notice when reviewing the output:

what goes wrong
-ss before -iseeks to the previous keyframe. An ultrafast screen capture has ~8s keyframe gaps, so the cut starts seconds early — on the wrong beat entirely.
-to after -imeasured on the filtered timeline, so a setpts speed-up stretches the window. A 30s target came out 57s.
trim=start=S:end=E,setpts=PTS-STARTPTS[,crop=W:H:X:Y],setpts=PTS/SPEED,fps=30,scale=...

trim runs on input timestamps, before setpts touches them.

Push in on small UI. Full-frame desktop UI is unreadable in a phone feed. Crop to the element (keep it 16:9) and rescale — a 1.2–1.4× push-in is usually enough. Measure the bounding box from a full-res extracted frame first; a crop that misses the thing you are pointing at is invisible until you review the cut.

Editorial rules for a silent autoplay feed:

  • No voiceover. Social video autoplays muted — everything must be in captions.
  • 3–5 words per caption, ~2.5s each, bottom third, white on a subtle scrim.
  • Speed-ramp the dead air (network waits, model latency) 3–8×; never hold a static frame.
  • The first 2 seconds decide completion. Open on the payoff of the first beat, never on an empty screen or a loading state.
  • End card: what it is, the license, the URL. 2–3s.
  • Downscale with flags=lanczos; export yuv420p + -movflags +faststart.

8. Music (optional)

If a bed is wanted, synthesise it — reference/music.sh builds one from ffmpeg sine sources. Never attach a track you found online: a promo clip is a commercial use, and "royalty-free" pages routinely mislabel licences. Generated audio has no rights question at all.

The recipe that sounds like music rather than a test tone: a four-chord progression with tight voice leading, each voice doubled by a second sine ~0.35% off for slow beating, then lowpass (warmth) → aecho (space) → tremolo (movement) → loudnorm. Put aresample=48000 after loudnorm, which otherwise leaves the output at 192kHz.

Verify what you can measure — -14 to -20 LUFS integrated, true peak under -1 dBTP, 48kHz stereo:

bash
ffmpeg -hide_banner -i bed.wav -af ebur128 -f null - 2>&1 | tail -12

Say plainly that you could not listen to it and ask the user to audition before posting. Levels and format are verifiable; whether it actually sounds good is not.

9. Tear down — required

bash
gcloud compute scp <VM>:/tmp/final.mp4 ./ --zone=<ZONE> --project=<PROJECT>
gcloud compute instances delete <VM> --zone=<ZONE> --project=<PROJECT> --quiet

Confirm the download opens locally before deleting. Then tell the user the VM is gone. If you are keeping it for retakes, say so explicitly and give them the delete command.


Honesty constraints

The recording is a claim about how the product behaves. So:

  • Never inject CSS/JS to make the UI fit or look better. If content clips, change the viewport (§1), not the app. A viewport that matches a real user's browser is the honest fix.
  • Never fake a state the app didn't produce. If a feature stays silent or empty during the take, that is the product's real behaviour — either give it genuine input that exercises it, or cut the beat.
  • Cutting and speeding up real footage is fine and expected. Staging output that the app never generated is not.

Reference

  • reference/setup.sh — VM package + font install
  • reference/stack.sh — Xvfb + app + Chrome bring-up
  • reference/take.mjs — annotated Playwright drive script with the MARK timeline
  • reference/edit.sh — segment / speed-ramp / caption / downscale pipeline

© oratis, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 5 other files in .claude/skills/cloud-screencast of oratis/LISA.

  • SKILL.md
  • reference/edit.sh
  • reference/music.sh
  • reference/setup.sh
  • reference/stack.sh
  • reference/take.mjs

Open the folder on GitHubat commit fa44994

Compare with similar skills

Cloud Screencast next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Cloud Screencast compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Cloud Screencast this skilloratis/LISA175—~3.1kAutomated safety check: WarnMIT
Cassette ModelCassette-Editor/oh-my-cassette1571 repos~374Automated safety check: PassMIT
Render Chatgpt Chatgooseworks-ai/goose-skills1.2k—~2.2kAutomated safety check: PassMIT
Browser Video Recordingnirholas/three.ws2271 repos~1.5kAutomated safety check: PassApache-2.0
Render Apple Notes Chatgooseworks-ai/goose-skills1.2k—~1.5kAutomated safety check: PassMIT
Demo Videojeremylongshore/tons-of-skills-marketplace2.8k—~953Automated safety check: PassMIT

Similar skills

  • Cassette Model

    Cassette-Editor/oh-my-cassette

    Show or change the Cassette editing model and thinking level for the current media session.

    157 GitHub starsUsed in 1 repo~374 tokens
    Media & CreativeAuto-check passed
  • Render Chatgpt Chat

    gooseworks-ai/goose-skills

    Assemble a ChatGPT chat-reveal video ad from a thread + timeline JSON — one continuous Playwright recording of a ChatGPT mobile chat (user types with the iOS keyboard up → taps send → keyboard…

    1.2k GitHub stars~2.2k tokensUpdated today
    Media & CreativeAuto-check passed
  • Browser Video Recording

    nirholas/three.ws

    Create polished 60 fps 4:3 4K browser screen-recording style videos from Codex in-app browser captures, with browser-only crop, natural macOS cursor styling, deliberate click choreography…

    227 GitHub starsUsed in 1 repo~1.5k tokens
    Media & CreativeAuto-check passed
  • Render Apple Notes Chat

    gooseworks-ai/goose-skills

    Assemble an Apple Notes list video ad from a note + end-card JSON — a frame-accurate fake iPhone screen recording of a short list being typed into Apple Notes (character by character, key pops…

    1.2k GitHub stars~1.5k tokensUpdated today
    Media & CreativeAuto-check passed
  • Demo Video

    jeremylongshore/tons-of-skills-marketplace

    Generate polished demo videos from a single prompt. An agent skill from jeremylongshore/tons-of-skills-marketplace.

    2.8k GitHub stars~953 tokensUpdated today
    Media & CreativeAuto-check passed
  • Automated Video Studio

    foryourhealth111-pixel/Vibe-Skills

    Turns footage, audio and a storyboard plan into a finished short video with FFmpeg jump-cuts, subtitle burn-in and a final polish pass.

    3.6k GitHub stars~838 tokensUpdated 1 mo ago
    Media & CreativeAuto-check passed

Questions about Cloud Screencast

What does Cloud Screencast do?

Record a clean product demo video of a web app on a disposable cloud VM — provision a GCE instance, install Xvfb + Chrome + ffmpeg + real fonts, deploy the app, drive the UI deterministically with…. Cloud Screencast is an agent skill from oratis/LISA. Record a clean product demo video of a web app on a disposable cloud VM — provision a GCE instance, install Xvfb + Chrome + ffmpeg + real fonts, deploy the app, drive the UI deterministically with Playwright over CDP while x11grab records, then cut the raw take into a social-ready clip with speed ramps and burned-in captions.

When should I use Cloud Screencast?

Cloud Screencast fits situations like: asked to record a demo / screencast / promo video; capture a reproducible app walkthrough — and especially when the local machine is unsuitable (personal bookmarks and profile chrome in frame; wrong window size; the app must start from a pristine state.

How do I install Cloud Screencast in Claude Code?

Run `npx skills add oratis/LISA --skill cloud-screencast -a claude-code`. Or copy the skill folder (.claude/skills/cloud-screencast in oratis/LISA) into .claude/skills/cloud-screencast in your project. Claude Code loads it when a task matches its description.

How do I install Cloud Screencast in Codex?

Run `npx skills add oratis/LISA --skill cloud-screencast -a codex`. Or copy the skill folder (.claude/skills/cloud-screencast in oratis/LISA) into .agents/skills/cloud-screencast in your project. Codex loads it when a task matches its description.

Can I use Cloud Screencast in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add oratis/LISA --skill cloud-screencast -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/cloud-screencast, .gemini/skills/cloud-screencast, .github/skills/cloud-screencast and .opencode/skills/cloud-screencast in your project.

What does Cloud Screencast need to run?

Going by SKILL.md and its folder, Cloud Screencast needs a shell and JavaScript for the scripts in its folder, the command-line tools its instructions call (gcloud, ssh and ffmpeg) and credentials named API_KEY. Our summary lists: Node.js; A Bash shell; A credential in API_KEY. Its frontmatter pre-approves these tools: Read, Write, Edit, Bash.

Does Cloud Screencast access the network?

SKILL.md contains no URLs. Its commands use ssh, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Cloud Screencast safe to install?

Our automated static check of SKILL.md flagged 1 warning(s): mentions a credentials file (ssh keys, cloud or package-manager tokens). Read the flagged lines before installing; the check is not a guarantee either way.

What licence does Cloud Screencast use?

Cloud Screencast is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Cloud Screencast use?

About 3.1k tokens (SKILL.md is roughly 12k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Cloud Screencast?

Skills that share tags, products or a category with Cloud Screencast: Cassette Model (Cassette-Editor/oh-my-cassette, 157 stars), Render Chatgpt Chat (gooseworks-ai/goose-skills, 1.2k stars), Browser Video Recording (nirholas/three.ws, 227 stars) and Render Apple Notes Chat (gooseworks-ai/goose-skills, 1.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Cloud Screencast?

oratis (a GitHub user) maintains it in oratis/LISA, which has 175 GitHub stars. The repository was last updated on October 7, 2026.

Source: oratis/LISA on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.